一种保持轨迹数据高可用性的隐式位置访问隐私保护技术

An algorithm of protecting hidden location visit privacy with high trajectory utility

随着带有签到服务的社交网络应用的普及,人们的轨迹信息不断被记录下来。通常发布轨迹数据以用于个性化推荐和活动挖掘,但是发布轨迹数据会导致用户的隐式位置访问隐私泄露。针对此问题提出了一种隐式位置访问隐私保护算法,其基本思想是采用位置替换和位置抑制技术来保护隐式位置访问隐私,同时设计了相关技术使得匿名轨迹数据与用户的行为模式相匹配。实验结果表明,算法可以有效地防止对真实数据集的推演攻击,同时保持轨迹数据高可用性。

With the spread of check-in service enabled social network applications,people’s trajectories are continuously recorded.Publishing trajectory data is usually used for personalized recommendationsand activity mining.However,publishing trajectory data makes users’hidden location visitsvulnerable to the inference attacks.Therefore,this paper proposes a privacy protection algorithm for hidden location visit.The basic idea is to adoptthe location replacement and location suppression technologies to protect the hidden location visit privacy.At the same time,the related technology is designed to match the anonymous trajectory data with the user behavior patterns.The experimental results show that our algorithms can efficiently prevent inference attacks onthe real datasets while preserving high utilityfor trajectory data.